Raspberry Pi Full Stack Course

Course Contents

What Will I Learn?

• → Setup the minimal Raspbian operating system to the RPi
• → Install the a Python virtual environment
• → Install and use Flask, a Python-based web micro-framework
• → Install and use uWSGI as the application server for Flask
• → Install and use Nginx light-weight web server
• → Use the RPi GPIOs as digital input and outputs
• → Use a DHT22 humidity and temperature sensor
• → Install and use the SQLite database
• → Use the Google Chart API to create visual representations of the sensor data
• → Use JQuery to add interactivity to web pages
• → Use Plotly for graphical analysis of sensor data
• → Install and configure a USB Wifi adaptor for your RPi

Requirements

• → A Raspberry Pi, any version
• → A Windows, Mac or Linux computer
• → A DHT11 or DHT22 sensor
• → An 5mm LED
• → Resistors
• → A breadboard and jumper wires
• → Access to the Internet
• → A USB Wifi dongle, if available

Who is the Target Audience?

• → Some experience in programming is useful
• → Python, Javascript (jQuery) and HTML is used throughout the course and some familiarity with basic programming concepts is expected
• → Ability to wire electronics
• → Ability to do independent research using online resources

Introduction to the Course

• → Introduction
• → About the Raspberry Pi
• → Components
• → Detailed List of Components you will need

The Operating System

• → Section Introduction
• → How to extract a tar.gz file
• → Installing mini Raspbian using Mac OS X
• → Installing mini Raspbian using Windows

Python and GPIOs

• → Section Introduction
• → Setup Python
• → GPIO basics
• → Make an LED blink
• → Read the status of a button
• → Read temperature and humidity from a digital sensor

Setup the Web Application Stack

• → Section Introduction
• → What is the Web application stack?
• → Install Nginx, the Web server
• → Install Flask and venv
• → Install uWSGI
• → Setup Upstart
• → About log files
• → Serving static assets and Skeleton
• → Styling our Web application with Skeleton
• → Debugging a Flask application

Building a Simple Flask Application on the Raspberry Pi

• → Section Intro
• → Show DHT22 sensor data in the browser
• → Install the SQLite3 database
• → Use a Python script to store sensor reading to the database
• → Automate sensor data logging with cron and SQLite3
• → Show historical sensor data in the browser

Improving Our Application with Date-Time Range Record Selector

• → Section Introduction
• → Selecting historical sensor data records with a time-date range
• → Define a date-time range in the URL
• → Timezones in Rasbian
• → Validating timestamps
• → Tidying up: refactor our application code

Improving the User Interface

• → Section Introduction
• → Adding date range radio buttons
• → Visualise sensor data with Google Charts
• → Install a datetime picker widgets
• → Setting up the datetime picker widget
• → Setting up time zones on the client side
• → Setting up time zones on the server side
• → Link the two pages of the application

Setup Cloud Charting and Analysis with Plotly

• → Section Introduction
• → Setup Plotly
• → Add Plotly links
• → Add Plotly support to the Flask application script

Other Useful Things to Know

• → Install and configure a Wifi USB dongle for wireless networking

Course Schedule

Overall Duration: 6 to 8 Weeks

Weekday: 1 hour per day (Mon-Fri)

Weekend: 2 hours per day (Sat-Sun)

Available Languages: English, Tamil

Mode of Learning: Live Online Meet

We undertake class training room sessions for students/professionals at your premises over weekend

Certification available

To know about training batch slot availability and fees, enquire now

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